Forecast of Cosmological Constraints with Type Ia Supernovae from the Chinese Space Station Telescope
Shi-Yu Li, Yun-Long Li, Tianmeng Zhang, Jozsef Vinko, Eniko Regos,, Xiaofeng Wang, Gaobo Xi, Hu Zhan

TL;DR
This paper simulates how the Chinese Space Station Telescope will detect and utilize Type Ia supernovae to improve measurements of cosmological parameters and understand dark energy.
Contribution
It presents a simulation framework for supernova detection with CSST and quantifies its potential to refine cosmological constraints compared to existing datasets.
Findings
CSST can detect up to ~1800 SNe Ia at z < 1.3.
Improved constraints on Ω_m and ω with CSST data.
Combining CSST with ground surveys enhances dark energy understanding.
Abstract
The 2-m aperture Chinese Space Station Telescope (CSST), which observes at wavelengths ranging from 255 to 1000 nm, is expected to start science operations in 2024. An ultra-deep field observation program covering approximately 10 square degrees is proposed with supernovae (SNe) and other transients as one of its primary science drivers. This paper presents the simulated detection results of type Ia supernovae (SNe Ia) and explores the impact of new datasets on the determinations of cosmological parameters. The simulated observations are conducted with an exposure time of 150 s and cadences of 10, 20, and 30 days. The survey mode covering a total of 80 observations but with a random cadence in the range of 4 to 14 days is also explored. Our simulation results indicate that the CSST can detect up to SNe Ia at z 1.3. The simulated SNe Ia are then used to constrain the…
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Taxonomy
TopicsGamma-ray bursts and supernovae · Solar and Space Plasma Dynamics · Stellar, planetary, and galactic studies
